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Working memory (WM) is one of the fundamental cognitive functions associated with the dorsolateral prefrontal cortex (DLPFC). However, we still know little about the neurochemical mechanisms of WM in the DLPFC. Here, we investigated WM-related dynamic neurometabolite and hemodynamic responses in the DLPFC. We measured Glx (glutamate+glutamine) and GABA alterations as well as blood-oxygen-level-dependent (BOLD) signal changes during a WM task combining functional magnetic resonance spectroscopy and functional magnetic resonance imaging (fMRI). In the DLPFC, we found that a 2-back task increased Glx concentrations and larger BOLD signal changes, and that these task-modulated Glx increases were positively correlated with task-induced regional activity. Importantly, task induced Glx changes in the DLPFC were associated with individual WM performance. Higher Glx increases were associated with increased DLPFC activation and lower WM task performance in the individuals. There were no changes in DLPFC GABA levels during WM processing. Our findings suggest that glutamatergic modulation in the DLPFC may play a critical role in WM processing and its performance.

BACKGROUND Depression is a substantial health and economic burden. In approximately one-third of patients, depression is resistant to first-line treatment; therefore, it is essential to find alternative treatments. Transcranial magnetic stimulation (TMS) is a neuromodulatory treatment involving the application of magnetic pulses to the brain that is approved in the United Kingdom and the United States in treatment-resistant depression. This trial aims to compare the clinical effectiveness, cost-effectiveness, and mechanism of action of standard treatment repetitive TMS (rTMS) targeted at the F3 electroencephalogram site with a newer treatment—a type of TMS called theta burst stimulation (TBS) targeted based on measures of functional brain connectivity. This protocol outlines brain imaging acquisition and analysis for the Brain Imaging Guided Transcranial Magnetic Stimulation in Depression (BRIGhTMIND) study trial that is used to create personalized TMS targets and answer the proposed mechanistic hypotheses. OBJECTIVE The aims of the imaging arm of the BRIGhTMIND study are to identify functional and neurochemical brain signatures indexing the treatment mechanisms of rTMS and connectivity-guided intermittent theta burst TMS and to identify imaging-based markers predicting response to treatment. METHODS The study is a randomized double-blind controlled trial with 1:1 allocation to either 20 sessions of TBS or standard rTMS. Multimodal magnetic resonance imaging (MRI) is acquired for each participant at baseline (before TMS treatment) with T1-weighted and task-free functional MRI during rest used to estimate TMS targets. For participants enrolled in the mechanistic substudy, additional diffusion-weighted sequences are acquired at baseline and at posttreatment follow-up 16 weeks after treatment randomization. Core data sets of T1-weighted and task-free functional MRI during rest are acquired for all participants and are used to estimate TMS targets. Additional sequences of arterial spin labeling, magnetic resonance spectroscopy, and diffusion-weighted images are acquired depending on the recruitment site for mechanistic evaluation. Standard rTMS treatment is targeted at the F3 electrode site over the left dorsolateral prefrontal cortex, whereas TBS treatment is guided using the coordinate of peak effective connectivity from the right anterior insula to the left dorsolateral prefrontal cortex. Both treatment targets benefit from the level of MRI guidance, but only TBS is provided with precision targeting based on functional brain connectivity. RESULTS Recruitment began in January 2019 and is ongoing. Data collection is expected to continue until January 2023. CONCLUSIONS This trial will determine the impact of precision MRI guidance on rTMS treatment and assess the neural mechanisms underlying this treatment in treatment-resistant depressed patients. CLINICALTRIAL ISRCTN Registry ISRCTN19674644; https://www.isrctn.com/ISRCTN19674644 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/31925

Background 1H-magnetic resonance spectroscopy (MRS) facilitates noninvasive diagnosis of pediatric brain tumors by providing metabolite profiles. Prospective studies of diagnostic accuracy and comparisons with conventional MRI are lacking. We aimed to evaluate diagnostic accuracy of MRS for childhood brain tumors and determine added clinical value compared with conventional MRI. Methods Children presenting to a tertiary pediatric center with brain lesions from December 2015 through 2017 were included. MRI and single-voxel MRS were acquired on 52 tumors and sequentially interpreted by 3 radiologists, blinded to histopathology. Proportions of correct diagnoses and interrater agreement at each stage were compared. Cases were reviewed to determine added value of qualitative radiological review of MRS through increased certainty of correct diagnosis, reduced number of differentials, or diagnosis following spectroscopist evaluation. Final diagnosis was agreed by the tumor board at study end. Results Radiologists’ principal MRI diagnosis was correct in 69%, increasing to 77% with MRS. MRI + MRS resulted in significantly more additional correct diagnoses than MRI alone (P = .035). There was a significant increase in interrater agreement when correct with MRS (P = .046). Added value following radiologist interpretation of MRS occurred in 73% of cases, increasing to 83% with additional spectroscopist review. First histopathological diagnosis was available a median of 9.5 days following imaging, with 25% of all patients managed without conclusive histopathology. Conclusions MRS can improve the accuracy of noninvasive diagnosis of pediatric brain tumors and add value in the diagnostic pathway. Incorporation into practice has the potential to facilitate early diagnosis, guide treatment planning, and improve patient care.

INTRODUCTION: Magnetic resonance imaging is a key investigation in the diagnosis of childhood solid tumours. Advanced techniques such as diffusion weighted imaging (DWI), magnetic resonance spectroscopy (MRS) and perfusion imaging probe the underlying cellular, chemical and vascular nature of the disease. Coupled with machine learning these scanning methods show improvement in diagnostic accuracy compared with conventional imaging. Advanced image analysis is not routinely available in hospitals. We present a clinical decision support system (CDSS) developed for advanced MR analysis and interpretation. METHOD: The CDSS was developed in house. The Children’s Cancer and Leukaemia Group Functional Imaging Group (CCLGFIG) Database, a national resource, was used to provide a repository of cases together with their advanced imaging and machine learning diagnostic classifiers. A new case is displayed alongside cases in the repository with known diagnoses, including summary statistics for relevant diagnostic categories. The CDSS was made available to radiologists, in their clinical environment for technical and clinical evaluation. Structured interviews were undertaken. The CDSS was developed as a computer app for multi-centre distribution. RESULTS: 436 MRS, 240 DWI and 85 perfusion cases were available for building repositories. Machine learning classifiers showed diagnostic accuracies for the major childhood brain tumour types of 85-95%. Comparison of MRS with a data repository was found to improve non-invasive diagnosis. Results from the CDSS can be uploaded to the CCLGFIG to support multicentre research. Positive feedback on the CDSS from clinicians included: ready access to advanced analysis; simple and efficient integration into clinical workflow; and assisted interpretation of advanced analysis. DISCUSSION: Advanced MR analysis techniques provide improved non-invasive diagnostic accuracy but are difficult to implement on clinical systems due to technical, infrastructure and training limitations. CONCLUSION: We have successfully released a CDSS for paediatric cancer within the hospital environment and assessed its suitability for clinical use.

BACKGROUND Metabolite concentrations are fundamental biomarkers of disease and prognosis. Magnetic resonance spectroscopy (MRS) is a noninvasive method for measuring metabolite concentrations; however, quantitation is affected by T2 relaxation. PURPOSE To estimate T2 relaxation times in pediatric brain tumors and assess how variation in T2 relaxation affects metabolite quantification. STUDY TYPE Retrospective. POPULATION Twenty-seven pediatric brain tumor patients (n = 17 pilocytic astrocytoma and n = 10 medulloblastoma) and 24 age-matched normal controls. FIELD STRENGTH/SEQUENCE Short- (30 msec) and long-echo (135 msec) single-voxel MRS acquired at 1.5T. ASSESSMENT T2 relaxation times were estimated by fitting signal amplitudes at two echo times to a monoexponential decay function and were used to correct metabolite concentration estimates for relaxation effects. STATISTICAL TESTS One-way analysis of variance (ANOVA) on ranks were used to analyze the mean T2 relaxation times and metabolite concentrations for each tissue group and paired Mann-Whitney U-tests were performed. RESULTS The mean T2 relaxation of water was measured as 181 msec, 123 msec, 90 msec, and 86 msec in pilocytic astrocytomas, medulloblastomas, basal ganglia, and white matter, respectively. The T2 of water was significantly longer in both tumor groups than normal brain (P

BACKGROUND: (1)H-magnetic resonance spectroscopy (MRS) facilitates noninvasive diagnosis of pediatric brain tumors by providing metabolite profiles. Prospective studies of diagnostic accuracy and comparisons with conventional MRI are lacking. We aimed to evaluate diagnostic accuracy of MRS for childhood brain tumors and determine added clinical value compared with conventional MRI. METHODS: Children presenting to a tertiary pediatric center with brain lesions from December 2015 through 2017 were included. MRI and single-voxel MRS were acquired on 52 tumors and sequentially interpreted by 3 radiologists, blinded to histopathology. Proportions of correct diagnoses and interrater agreement at each stage were compared. Cases were reviewed to determine added value of qualitative radiological review of MRS through increased certainty of correct diagnosis, reduced number of differentials, or diagnosis following spectroscopist evaluation. Final diagnosis was agreed by the tumor board at study end. RESULTS: Radiologists’ principal MRI diagnosis was correct in 69%, increasing to 77% with MRS. MRI + MRS resulted in significantly more additional correct diagnoses than MRI alone (P = .035). There was a significant increase in interrater agreement when correct with MRS (P = .046). Added value following radiologist interpretation of MRS occurred in 73% of cases, increasing to 83% with additional spectroscopist review. First histopathological diagnosis was available a median of 9.5 days following imaging, with 25% of all patients managed without conclusive histopathology. CONCLUSIONS: MRS can improve the accuracy of noninvasive diagnosis of pediatric brain tumors and add value in the diagnostic pathway. Incorporation into practice has the potential to facilitate early diagnosis, guide treatment planning, and improve patient care.

BACKGROUND: (1)H-Magnetic Resonance Spectroscopy (MRS) facilitates non-invasive diagnosis of pediatric brain tumors through providing metabolite profiles. Prospective studies of diagnostic accuracy and comparisons with conventional Magnetic Resonance Imaging (MRI) are lacking. AIM: To evaluate diagnostic accuracy of qualitative radiological review of MRS for childhood brain tumors, and determine added clinical value compared with conventional MRI. METHODS: Children presenting to a Tertiary Pediatric Centre with brain lesions from December 2015-17 were eligible for inclusion. MRI and single-voxel MRS were acquired on 52 tumors and sequentially interpreted by three radiologists, blind to histopathology. Proportions of correct diagnoses and inter-rater agreement at each stage were compared. Cases were reviewed to determine added value through increased certainty of correct diagnosis, reduced number of differentials, or diagnosis following spectroscopist evaluation. Final diagnosis was agreed by the Tumor Board (TB) at study end. RESULTS: Radiologists’ principal MRI diagnosis was correct in 69%, increasing to 77% with MRS. MRI+MRS resulted in significantly more additional correct diagnoses than MRI alone (p=0.035). There was significant increase in inter-rater agreement when correct with MRS (p=0.046). Added value following radiologist interpretation of MRS occurred in 73% of cases, increasing to 83% with additional spectroscopist review. First histopathological diagnosis was available a median 9.5 days following imaging, with 25% of all patients managed without conclusive histopathology. CONCLUSION: MRS can improve accuracy of non-invasive diagnosis of pediatric brain tumors and add value in the diagnostic pathway. Incorporation into practice has potential to facilitate early diagnosis, guide treatment planning and improve patient care.

Objective To explore the small-world properties of brain functional networks in patients with obstructive sleep apnea−hypopnea syndrome (OSAHS) to aid diagnosis. Methods A total of 29 OSAHS patients and 26 matched healthy volunteers were scanned with blood oxygen level−dependent functional magnetic resonance imaging (BOLD-fMRI) separately, and the whole brain was divided into 90 districts via automated anatomical labeling. The matrix Z was then built through a Fisher Z transformation. Two-sample t tests were applied to evaluate the changes in small-world properties in OSAHS patients compared to the control group. The properties included Eglobal, Elocal, and small-world parameters Lp, Cp, γ, λ, and σ. Results Both groups satisfied the small-world properties (σ > 1) within the sparsity range of 0.1–0.2. However, compared with the control group, the OSAHS group performed significantly lower in Cp, Elocal, and Eglobal (p Conclusion Both healthy and OSAHS patients exhibited small-world properties in functional networks, but a subset of these small-world properties in OSAHS patients performed differently. These changes will not only provide a new perspective for pathophysiological mechanisms of OSAHS but will also help in understanding the disease in terms of whole-brain functional networks.

Objective To develop and assess a short-duration JPRESS protocol for detection of overlapping metabolite biomarkers and its application to paediatric brain tumours at 3 Tesla. Materials and methods The short-duration protocol (6 min) was optimised and compared for spectral quality to a high-resolution (38 min) JPRESS protocol in a phantom and five healthy volunteers. The 6-min JPRESS was acquired from four paediatric brain tumours and compared with short-TE PRESS. Results Metabolite identification between the 6- and 38-min protocols was comparable in phantom and volunteer data. For metabolites with Cramer–Rao lower bounds > 50%, interpretation of JPRESS increased confidence in assignment of lactate, myo-Inositol and scyllo-Inositol. JPRESS also showed promise for the detection of glycine and taurine in paediatric brain tumours when compared to short-TE MRS. Conclusion A 6-min JPRESS protocol is well tolerated in paediatric brain tumour patients. Visual inspection of a 6-min JPRESS spectrum enables identification of a range of metabolite biomarkers of clinical interest. Electronic supplementary material The online version of this article (10.1007/s10334-018-0716-6) contains supplementary material, which is available to authorized users.

MRS thermometry has been utilized to measure temperature changes in the brain, which may aid in the diagnosis of brain trauma and tumours. However, the temperature calibration of the technique has been shown to be sensitive to non-temperature-based factors, which may provide unique information on the tissue microenvironment if the mechanisms can be further understood. The focus of this study was to investigate the effects of varied protein content on the calibration of MRS thermometry at 3 T, which has not been thoroughly explored in the literature. The effects of ionic concentration and magnetic field strength were also considered. Temperature reference materials were controlled by water circulation and freezing organic fixed-point compounds (diphenyl ether and ethylene carbonate) stable to within 0.2 °C. The temperature was measured throughout the scan time with a fluoro-optic probe, with an uncertainty of 0.16 °C. The probe was calibrated at the National Physical Laboratory (NPL) with traceability to the International Temperature Scale 1990 (ITS-90). MRS thermometry measures were based on single-voxel spectroscopy chemical shift differences between water and N-acetylaspartate (NAA), Δ(H20-NAA), using a Philips Achieva 3 T scanner. Six different phantom solutions with varying protein or ionic concentration, simulating potential tissue differences, were investigated within a temperature range of 21–42 °C. Results were compared with a similar study performed at 1.5 T to observe the effect of field strengths. Temperature calibration curves were plotted to convert Δ(H20-NAA) to apparent temperature. The apparent temperature changed by −0.2 °C/% of bovine serum albumin (BSA) and a trend of 0.5 °C/50 mM ionic concentration was observed. Differences in the calibration coefficients for the 10% BSA solution were seen in this study at 3 T compared with a study at 1.5 T. MRS thermometry may be utilized to measure temperature and the tissue microenvironment, which could provide unique unexplored information for brain abnormalities and other pathologies.

Molecular subgroup is now influencing risk stratification and disease management in medulloblastoma. Tissue metabolite profiles have shown promise in identifying the four consensus subgroups. A smaller number of metabolites can be measured non-invasively in patients using magnetic resonance spectroscopy (MRS). We investigated if a classifier constructed from tissue metabolites could be applied to in-vivo metabolite profiles to accurately predict subgroup non-invasively. Machine learning was used to construct a classifier with tissue concentrations from 10 metabolites reliably detected in-vivo. Retrospectively acquired diagnostic in-vivo MRS was available for 37 cases from four treatment centres. Although we identified WNT tumours by the presence of GABA with 100% accuracy in tissue, GABA was not reliability quantified in this in-vivo dataset. Therefore the classifier was developed using tissue profiles of known molecular subgroup (determined using DNA methylation array) from group 3(n=20), group 4(n=34) and SHH(n=23). The cross-validated accuracy of the tissue classifier was 86%. When applied to in-vivo metabolite profiles, subgroup was predicted non-invasively with an overall accuracy of 76%. Group 3 had the highest proportion of incorrectly classified cases (4/11), followed by SHH (2/10), and group 4 (3/16), largely due to differences in measuring lipids, glutamate, glutamine and hypotaurine in-vivo. We have established the feasibility of non-invasive metabolite profiling to identify medulloblastoma subgroups. With the ongoing optimization of MRS to target specific metabolites including GABA, we can further improve accuracy. Rapid, non-invasive preoperative diagnosis of subgroup will offer opportunities to stratify early therapeutic intervention especially surgery, avoiding long-term sequalae and improving quality of survival.

MRS thermometry has been utilized to measure temperature changes in the brain, which may aid in the diagnosis of brain trauma and tumours. However, the temperature calibration of the technique has been shown to be sensitive to non-temperature-based factors, which may provide unique information on the tissue microenvironment if the mechanisms can be further understood. The focus of this study was to investigate the effects of varied protein content on the calibration of MRS thermometry at 3 T, which has not been thoroughly explored in the literature. The effects of ionic concentration and magnetic field strength were also considered. Temperature reference materials were controlled by water circulation and freezing organic fixed-point compounds (diphenyl ether and ethylene carbonate) stable to within 0.2 °C. The temperature was measured throughout the scan time with a fluoro-optic probe, with an uncertainty of 0.16 °C. The probe was calibrated at the National Physical Laboratory (NPL) with traceability to the International Temperature Scale 1990 (ITS-90). MRS thermometry measures were based on single-voxel spectroscopy chemical shift differences between water and N-acetylaspartate (NAA), Δ(H20-NAA), using a Philips Achieva 3 T scanner. Six different phantom solutions with varying protein or ionic concentration, simulating potential tissue differences, were investigated within a temperature range of 21-42 °C. Results were compared with a similar study performed at 1.5 T to observe the effect of field strengths. Temperature calibration curves were plotted to convert Δ(H20-NAA) to apparent temperature. The apparent temperature changed by -0.2 °C/% of bovine serum albumin (BSA) and a trend of 0.5 °C/50 mM ionic concentration was observed. Differences in the calibration coefficients for the 10% BSA solution were seen in this study at 3 T compared with a study at 1.5 T. MRS thermometry may be utilized to measure temperature and the tissue microenvironment, which could provide unique unexplored information for brain abnormalities and other pathologies.

1H MRS thermometry has been investigated for brain trauma and hypothermia monitoring applications but has not been explored in brain tumours. The proton resonance frequency (PRF) of water is dependent on temperature but is also influenced by microenvironment factors, such as fast proton exchange with macromolecules, ionic concentration and magnetic susceptibility. 1H MRS has been utilized for brain tumour diagnostic and prognostic purposes in children; however, the water PRF measure may provide complementary information to further improve characterization. Water PRF values were investigated from a repository of MRS data acquired from childhood brain tumours and children with apparently normal brains. The cohort consisted of histologically proven glioma (22), medulloblastoma (19) and control groups (28, MRS in both the basal ganglia and parietal white matter regions). All data were acquired at 1.5 T using a short TE (30 ms) single voxel spectroscopy (PRESS) protocol. Water PRF values were calculated using methyl creatine and total choline. Spectral peak amplitude weighted averaging was used to improve the accuracy of the measurements. Mean PRF values were significantly larger for medulloblastoma compared with glioma, with a difference in the means of 0.0147 ppm (p < 0.05), while the mean PRF for glioma was significantly lower than for the healthy cohort, with a difference in the means of 0.0061 ppm (p < 0.05). This would suggest the apparent temperature of the glioma group was ∼1.5 °C higher than the medulloblastomas and ∼0.7 °C higher than a healthy brain. However, the PRF shift may not reflect a change in temperature, given that alterations in protein content, microstructure and ionic concentration contribute to PRF shifts. Measurement of these effects could also be used as a supplementary biomarker, and further investigation is required. This study has shown that the water PRF value has the potential to be used for characterizing childhood brain tumours, which has not been reported previously. © 2014 The Authors. NMR in Biomedicine published by John Wiley & Sons, Ltd.

Prostate cancer detection using diffusion-weighted imaging is highly affected by the accuracy of the apparent diffusion coefficient (ADC) values in an image. Echo planar imaging (EPI) is a fast sequence commonly used for diffusion imaging but has inherent magnetic susceptibility and chemical shift artefacts associated. A diffusion sequence that is less affected by these artefacts is therefore advantageous. The half-Fourier acquisition single-shot turbo spin-echo (HASTE) sequence was chosen. The diffusion sequences were compared in image quality, repeatability of the ADC value and the effect on the ADC value with varied b values. Eight volunteers underwent three scans of each sequence, on a 1.5-T Siemens system, using b values of 0, 150, 300, 450, 600, 750, 900 and 1000 s/mm(2). ADC maps were created to address the reproducibility of the ADC value when using two b values compared to eight b values. The ADC value using all b values with the HASTE sequence gave the best performance in all tested categories. Both sequences gave significantly different ADC mean values for two b values compared to when using eight b values (P.05) suggesting larger error is present when using two b values. HASTE was shown to be an improvement over EPI in terms of repeatability, signal variation within a region of interest and standard deviation over the volunteer set. The improved accuracy of the ADC value in the HASTE sequence makes it potentially a more sensitive tumor detection technique.